doc/book/en/development/devweb/facets.rst
author Aurelien Campeas <aurelien.campeas@logilab.fr>
Thu, 15 Apr 2010 16:14:23 +0200
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permissions -rw-r--r--
[doc/book] rework the templates chapter (wipe out horrible example, talk more about structure)
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The facets system
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-----------------
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XXX feed me more (below is the extracted of adim blog)
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Recently, for internal purposes, we've made a little cubicweb application to
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help us
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organizing visits to find new office locations. Here's an *excerpt* of the
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schema:
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.. sourcecode:: python
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  class Office(WorkflowableEntityType):
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      price = Int(description='euros / m2 / HC / HT')
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      surface = Int(description='m2')
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      description = RichString(fulltextindexed=True)
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      has_address = SubjectRelation('PostalAddress', cardinality='1?', composite='subject')
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      proposed_by = SubjectRelation('Agency')
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      comments = ObjectRelation('Comment', cardinality='1*', composite='object')
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      screenshots = SubjectRelation(('File', 'Image'), cardinality='*1',
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                                    composite='subject')
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The two other entity types defined in the schema are `Visit` and `Agency` but we
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can also guess from the above that this application uses the two cubes
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`comment`_ and
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`addressbook`_ (remember, cubicweb is only a game where you assemble cubes !).
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While we know that just defining the schema in enough to have a full, usable,
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(testable !) application, we also know that every application needs to be
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customized to fulfill the needs it was built for. So in this case, what we
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needed most was some custom filters that would let us restrict searches
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according
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to surfaces, prices or zipcodes. Fortunately for us, Cubicweb provides the
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**facets** (image_) mechanism and a few base classes that make the task quite
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easy:
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.. sourcecode:: python
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  class PostalCodeFacet(RelationFacet):
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      __regid__ = 'postalcode-facet'             # every registered class must have an id
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      __select__ = implements('Office')   # this facet should only be selected when
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                                          # visualizing offices
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      rtype = 'has_address'               # this facet is a filter on the entity linked to
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                                          # the office thrhough the relation
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                                          # has_address
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      target_attr = 'postalcode'          # the filter's key is the attribute "postal_code"
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                                          # of the target PostalAddress entity
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This is a typical `RelationFacet`: we want to be able to filter offices
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according
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to the attribute `postalcode` of their associated `PostalAdress`. Each line in
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the class is explained by the comment on its right.
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Now, here is the code to define a filter based on the `surface` attribute of the
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`Office`:
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.. sourcecode:: python
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  class SurfaceFacet(AttributeFacet):
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      __regid__ = 'surface-facet'              # every registered class must have an id
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      __select__ = implements('Office') # this facet should only be selected when
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                                        # visualizing offices
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      rtype = 'surface'                 # the filter's key is the attribute "surface"
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      comparator = '>='                 # override the default value of operator since
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                                        # we want to filter according to a
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                                        # minimal
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                                        # value, not an exact one
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      def rset_vocabulary(self, ___):
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          """override the default vocabulary method since we want to hard-code
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          our threshold values.
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          Not overriding would generate a filter box with all existing surfaces
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          defined in the database.
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          """
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          return [('> 200', '200'), ('> 250', '250'),
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                  ('> 275', '275'), ('> 300', '300')]
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And that's it: we have two filter boxes automatically displayed on each page
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presenting more than one office. The `price` facet is basically the same as the
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`surface` one but with a different vocabulary and with ``rtype = 'price'``.
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(The cube also benefits from the builtin google map views defined by
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cubicweb but that's for another blog).
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.. _image: http://www.cubicweb.org/image/197646?vid=download
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.. _comment: http://www.cubicweb.org/project/cubicweb-comment
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.. _addressbook: http://www.cubicweb.org/project/cubicweb-addressbook
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CubicWeb has this really nice builtin `facet`_ system to
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define restrictions `filters`_ really as easily as possible.
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We've just added two new kind of facets in CubicWeb :
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- The **RangeFacet** which displays a slider using `jquery`_
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  to choose a lower bound and an upper bound. The **RangeWidget**
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  works with either numerical values or date values
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- The **HasRelationFacet** which displays a simple checkbox and
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  lets you refine your selection in order to get only entities
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  that actually use this relation.
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.. image :: http://www.cubicweb.org/Image/343498?vid=download
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Here's an example of code that defines a facet to filter
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musical works according to their composition date:
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.. sourcecode:: python
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    class CompositionDateFacet(DateRangeFacet):
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        # 1. make sure this facet is displayed only on Track selection
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        __select__ = DateRangeFacet.__select__ & implements('Track')
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        # 2. give the facet an id required by CubicWeb)
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        __regid__ = 'compdate-facet'
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        # 3. specify the attribute name that actually stores the date in the DB
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        rtype = 'composition_date'
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And that's it, on each page displaying tracks, you'll be able to filter them
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according to their composition date with a jquery slider.
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All this, brought by CubicWeb (in the next 3.3 version)
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.. _facet: http://en.wikipedia.org/wiki/Faceted_browser
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.. _filters: http://www.cubicweb.org/blogentry/154152
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.. _jquery: http://www.jqueryui.com/
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To use **HasRelationFacet** on a reverse relation add ``role = 'object'`` in
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it's definitions.